An Interview with Emily Chen

by Andy Kriebel

We’re bringing you a brand new series today, exploring life at the Data School through the eyes (or rather, mouths) of some of the latest and greatest students from the Data School – both past and present. In part 1 of our “An interview with…” series, we spoke to Emily Chen about her experiences as part of DS1: the challenges, benefits and everything in between. If you’re thinking of a career in data analytics, make sure to follow the whole series to get an understanding of what goes on at the Data School and what could be in it for you. So without further ado, let’s get started…

Thanks for speaking with us today Emily! To kick things off, what appealed to you the most about joining the Data School?

“Oh, a lot of things! I was moving from a career in eCommerce; I felt like being on the data side was more exciting and strategic than sitting on the business side. I guess I would say those are the two key things for me. When you sit on the business side it can be hard to know what’s really happening. You make decisions based on what people tell you, your analytics team for example. But by being on the side of data I know what’s right, I can make decisions based on this great idea that I have, so I feel more comfortable that my decision was right. I guess that served as a sort of litmus test and I know I made the right decision. I actually turned down a good job opportunity from eBay but I can definitely say it was the best career decision I ever made.”

 So once you got started, what was an average week like for you at the Data School?

 “It was definitely high-energy! Once we got into the rhythm, we’d have a client brief Monday morning, begin collecting requirements, collecting data and reviewing. That would be days 1 and 2. By day 2 to 3 you’d have an idea of where you want to go with the data, and start playing and experimenting to get the vision you want. Obviously it doesn’t always run smoothly so sometimes you’d get roadblocks, and it would often get quite chaotic between Wednesday and Thursday finding the right solutions. Thursday was usually when we started to create the vizzes and look to complete our work, which would you know sometimes be a bit of a mad dash! There might be access issues, clients might be busy, stuff like that. When Friday hits its presentation day and you want something the client is going to be happy with; you want to know you’ve answered all their questions.”

 What was your favourite thing about being a part of DS1?

“The ability to get world-class learning. It’s unparalleled, almost: we have 3 Tableau Zen Masters and an Alteryx Ace, which helps me know I’m learning the right thing from the best people. I think that’s kind of rare actually, where else do you get to learn from people that good? Quite often when you’re working you’re just ‘doing your job’, you don’t get an opportunity to learn best practice. But with the Data School it’s like being in a candy store – there’s no limitations and you learn as much as you can and want to.”

 What were some of your biggest challenges?

“For me, it was probably getting into the mindset of a thinking like a programmer. It’s a specific skill set and not one that I had been trained in previously. Getting into the mind-set of a Tableau developer was difficult, but I had enough people around to help me grow accustomed to it and overcome it.”

 What was the best piece of advice given to you by your Data School coaches?

“It was something Andy [Kriebel] said to me; one day I asked him why we blogged – or rather ‘I don’t get why we blog’ is what I said – because at the time I was finding the blogging a challenge, and I was finding it harder to market myself as I’m a very private person and I’d only ever really known about marketing a brand. You have to have a certain level of confidence to really showcase what you’ve made and how well, so it was something I had to adopt to. But he said to me “The reason I blog is because I learn something new every day, and the blogging process helps build a reference for myself so I actually remember it.” That really stuck with me and it didn’t take me long to find out how true that was.”

You mentioned you found blogging challenging, but it’s a large part of the learning process. How rewarding did it feel to overcome those challenges?

“Personally, I really didn’t think it would be as challenging as it was. However, like Andy told me, it’s the absolute best way to solidify your learning because it makes you articulate and consider every part of what you’re working on, and ultimately it makes you stronger”.

The Tableau & Alteryx community is a pretty active one, how have they helped you?

“When I met the community at the Tableau Conference, even if you didn’t know someone it was like they were coming to us with… how do I put this… kinda like a warm hug! (laughs) It was fantastic. We saw like to like. The community is where you know each other through your work – everyone is active, learning, sharing – and as a result I grew to feel comfortable sharing what we’ve learned”.

How was it sharing your learning experience as part of a group? Did you find yourself helping other members and vice versa?

“It was a really big part of it, for sure. The environment was great – we would have 8 people learning each other’s styles and the way they think, which makes you think in a completely different way. It was a collaborative experience and I learned a lot from it. Even if you were, you know, diligent yourself, if you’re there with 8 other people it’s a much more rhythmic process”.

How did the Data School set you up for success?

“I’d say it’s built up my knowledge in two ways – it’s given me access to build my own analytical knowledge, and access to the people who will know the answer if I don’t. It means that there are no limitations on anything I want to do in the world of data analytics, it’s just a matter of what I choose to do”.

For someone undecided about applying, what would you say to them?

“Hmm… okay so take this job if you like this: if you like everything in the world; and if you find everything interesting. I know I can find the little interesting details in anything. If you like quantifying weird things, things that there is a logical concept behind it. It’s a job for left- and right-brain thinkers. You must enjoy problem solving. If you like how pieces fit together, it’ll be a perfect job for you. I can’t think of a better job in the world if you like all of those things. For me, it’s perfect; I would 100% make that decision again.”

That sounds pretty convincing to us!

(Laughs) did I convince you guys? Good! I think a lot of it is about marrying the science and art of data. I remember a quote, something like “Nobody ever remembers a story if it doesn’t resonate with them.” As in; you want to make sure it’s approachable for the readers otherwise no one will read it, let alone remember it!

 

After graduating the Data School, Emily moved onto a 6-month placement where she could put her Tableau and Alteryx skills to the test in a real working environment. We also got the chance to speak with Tom Bache – Emily’s current employer – on her progress since graduating, and how the skills she’s learnt at the Data School have transferred over into the working world.

Did you notice an immediate impact from Emily since she joined the company?

“It’s been good; she’s adapted really quickly. You only have 6-months with these placements so you don’t want to spend 3 months explaining how the business runs. But she’s had an immediate impact, based on being able to ‘plug in and play’ given the data. She joined in September/October time and by the end of December she’d already delivered a massive project for us which was fantastic. It’s great to have the technical skill and the ability to be able to do that”.

How do you think the Data School has prepared them for their placements?

“Yeah really well. The Tableau expertise has been helpful from both having it in the building and within my own team. And from a training perspective we get the knowledge from the team not only in the Data School but the wider team at the InfoLab as well, so that’s definitely been really useful for us”.

Had you guys used Tableau previously?

“Yeah, we’d used it for 12 months prior or so; we’ve used it extensively and had advanced training. We’d used it a lot but we’re able to now give Emily some really cool projects to visualize data in the right way. It helps us expand our number of business functions and also what we’re able to utilize data with”.

Have you noticed any particular strengths Emily’s shown?

“She has an innate ability to visualize data in a clear and concise way. We sometimes overcomplicate Tableau; we put it on a laptop or iPad and it looks a bit weird, but she gives clarity on the visualization of the data which has been really good. There’s also now an understanding that you can throw a project over her way and she’ll get it done, which is important given the process is only 6 months so we don’t have too much time to spend on training”.

Would you look to use the Data School again if looking for new consultants?

“I’ve actually got someone coming in next month! Nai from DS2 is joining so we’re really looking forward to that”.

So that’s a yes then!

“(laughs) Yeah, I wish Emily could stay for longer now that she’s understanding the business, it’s a bit frustrating in that respect from the business end but we’re excited to have another Data School student on the way”.

Will Emily help with the handover then?

Yeah, well I hope so! (laughs)

Next up in our “An interview with…” series, we talk to Rob Suddaby of the current Data School cohort on his experience with data prior to joining the Data School, and how the course has changed his views on the subjects of data visualization and Tableau.